Data Engineer Amsterdam

Vacancy: Data Engineer Amsterdam

• Do you enjoy working with open-source data technologies and understanding what happens beneath the abstraction layers?
• Would you like to optimise the performance, architecture, cost and data quality of a platform that reaches tens of millions of people?
• Do you want the technical scale of a large platform with the influence of a medium-sized company, where you can introduce ideas without moving through endless layers of decision-making?
• And do you say yes to a salary up to €80.000, flexible working hours, hybrid working from one of the coolest offices in Amsterdam with a lot of events?

Sounds like you? Keep reading.

Your employer: Global reach with the influence of a medium-sized company

You join a medium-sized, internationally operating technology company in Amsterdam that builds a digital experience around one of humanity's biggest passions in entertainment. The platform reaches tens of millions of people worldwide, which gives you the technical scale and impact of a much larger organisation while you work somewhere small enough to actually influence how things are built.

Behind that global experience sits a modern data platform. Behavioural and product data has to be processed, enriched and transformed, recommendation models need reliable input, and teams across the company depend on data they can trust. Because the organisation works mainly with open-source technology and owns its architecture, you are not limited to clicking together managed cloud services: you can dig into how systems really work and improve them.

The culture is open, informal and social, in an international environment with more than twenty nationalities and English as the working language. There is a lot of freedom, flexible hours and little micromanagement. Because of their business, they have a lot of company events, party’s and more social activities.

Your role: Data Engineer Amsterdam

As a Data Engineer Amsterdam you will join a backend team of six engineers and help take the existing data platform to its next technical level. Because the team is compact, your work does not disappear into a large department: an improvement to a pipeline, query or data model can go live quickly and have a visible effect across the organisation.

Your focus is on building and improving ETL processes, Airflow pipelines, analytical data models and production data services, and on making the platform faster, more reliable and more cost-efficient through better query performance, storage, transformations and architecture. The platform already runs on a modern stack, so you spend your time on optimisation and new ideas rather than rebuilding an outdated data warehouse. You also work closely with the machine-learning engineers behind personalisation and recommendations, turning raw data into reliable datasets, features and data marts. Because the platform reaches tens of millions of people, better data does not just improve an internal report, it directly improves how a global audience experiences the product.

The stack includes Python, Airflow, analytical databases, Kafka, Docker, Kubernetes and GCP, with most development in Python and Scala to a smaller extent. You do not need every technology on day one; what matters is that you understand the fundamentals behind analytical databases, data pipelines and distributed systems, and can explain the trade-offs you make.

What is required?

• 3+ years of experience in data engineering or software engineering
• Professional experience building ETL processes, batch pipelines or analytical data solutions
• Strong programming skills in Python and/or Scala
• Experience with workflow orchestration, such as Airflow
• Understanding of analytical databases, data modelling and query optimisation
• A drive to understand how technologies work beneath the abstraction layer
• Professional fluency in English
• Experience with Kafka, Kubernetes, dbt, data-quality tooling or ML data preparation is a plus

What is offered?

• Salary up to €80.000 gross per year, based on experience and impact
• The influence of a platform reaching tens of millions of people
• Considerable freedom to introduce ideas and improve the data architecture
• Flexible working hours and 2 working-from-home days
• 25 holidays
• Pension scheme and travel allowance
• MacBook or laptop of your choice
• Learning budget of €1.500 every two years
• Daily breakfast and freshly prepared lunch
• Regular events and Friday drinks in one of the coolest offices in Amsterdam

Would you like to improve a modern data platform and see your work reach tens of millions of people?